Hi there!

I am a PhD student at the University of Exeter. My research interests include natural language processing, computer vision, bioinformatics (RNA modeling), etc. Please find the details of my study in the following sections. Find me on GitHub or Google Scholar.

Research Topics

• Textual Adversarial Attack/Defense
• Sentiment (Coherency) Analysis
• bio-RNA Sequence pretraining & modeling
• Code language modeling
• Diffusion models

First-author Publications

[CCF A] H Yang, K Li. Boosting Text Augmentation via Hybrid Instance Filtering Framework (ACL 2023 Findings)

[CCF B] H Yang, K Li. InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction Operators (EMNLP 2023 Findings)

[CCF B] H Yang, K Li. PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysis (CIKM 2023)

[CCF A] K Li, H Yang, W Visser. Evolutionary Multi-Task Injection Testing on Web Application Firewalls (IEEE TSE 2023)

[CCF C] B Zeng, H Yang, S Liu, M Xu. Learning for target-dependent sentiment based on local context-aware embedding (The Journal of Supercomputing 2022)

[CCF C] H Yang, B Zeng, JH Yang, Y Song, R Xu. A multi-task learning model for Chinese-oriented aspect polarity classification and aspect term extraction (Neurocomputing 2021).

H Yang, K Li. Reactive Perturbation Defocusing for Textual Adversarial Defense (Preprint 2023)

H Yang, K Li. Improving Implicit Sentiment Learning via Local Sentiment Aggregation (Preprint 2021)

B Zeng, H Yang, R Xu, W Zhou, X Han. LCF: A local context focus mechanism for aspect-based sentiment classification (Applied Sciences 2019).

K Li is my PhD’s supervisor. B Zeng was my master’s supervisor.

Co-authored Publications

[CCF C] M Xu, B Zeng, H Yang, J Chi, J Chen, H Liu. Combining dynamic local context focus and dependency cluster attention for aspect-level sentiment classification (Neurocomputing 2022)

Toy Demos:

Aspect-based sentiment analysis (ABSA)

Super-resolution anime diffusion

Open-source Repositories

• PyABSA: State-of-the-art models and simplified interface for ABSA
• FindFile: A simple tool to help find your file wherever it locates
• Metric-Visualizer: Help you to easily and quickly make academic plots, e.g., box and trajectory plots
• BoostAug: it can achieve at most 5% absolute improvement based on full-scale datasets for most models.
• InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction Operators.
• Adversarial defense: This work propose an effective adversarial defense method for textual adversarial defense.
• ABSA DPT: This is a web-based ABSA dataset annotation tool that can help you easily make an ABSA dataset and train it using PyABSA.
• [More works are going to be published]

Education

• 2021.9 - 2025.9 CS PhD student in AI/NLP, University of Exeter, UK
• 2018.9 - 2021.6 CS Master in AI/NLP, South China Normal University, China
• 2014.9 - 2018.6 CS Bachelor, Yangtze University, China

Awards

• 2020.9 Chinese National Graduate Scholarship
• 2018.6 Outstanding Graduate of Yangtze University

Community Contribution